Background: Azo dyes are the most widely used synthetic colorants in the textile, food, pharmaceutical, cosmetic, and other industries, accounting for nearly 70% of all dyestuffs consumed. Recently, much research attention has been paid to efficient monitoring of these hazardous chemicals and their related metabolites because of their potentially harmful effect on environmental issues. In contrast to the complex and expensive instrumental procedures, the detection system based on the quantum dots (QDs) with the superior optochemical properties provides a new era in the pollution sensing and prevention.
Methods: We have developed a QD-enzyme hybrid system to probe methyl red (MR) in aqueous solutions using a fluorescence quenching procedure.
Results: The azoreductase enzyme catalyzed the reduction of azo group in MR, which can efficiently decrease the Förster resonance energy transfer between the QDs and MR molecules. The correlation between the QDs photoluminescence recovery and MR enzymatic decolorization at the neutral phosphate buffer permitted the creation of a fluorescence quenching-based sensor. The synthesized biosensor can be used for the accurate detection of MR in a linear calibration over MR concentrations of 5-84 μM, with the limit of detection of 0.5 μM in response time of three minutes.
Conclusion: Our findings revealed that this fluorometric sensor has the potential to be successfully applied for monitoring a wide linear range of MR concentration with the relative standard deviation of 4% rather than the other method.
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http://dx.doi.org/10.29252/ibj.25.1.8 | DOI Listing |
Sci Rep
January 2025
College of Electrical and Information Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, People's Republic of China.
The development and modification of grouting materials constitute crucial factors influencing the effectiveness of grouting. Given the pivotal role of water in the hydration of cement-based composite materials and construction processes, this study proposes an exploratory approach using green, economical magnetized water technology to enhance the performance of cement grouts. The research systematically investigates the effects of magnetized water on the fundamental grouting properties (stability, rheological behavior, and stone body strength) of cement grouts, prepared under varying magnetization conditions (including magnetic intensity, water flow speed, and cycle times).
View Article and Find Full Text PDFNat Commun
January 2025
Shanghai Key Lab of Chemical Assessment and Sustainability, School of Chemical Science and Engineering, Tongji University, Shanghai, China.
Photocatalytic overall water splitting is a promising approach for a sustainable hydrogen provision using solar energy. For sufficient solar energy utilization, this reaction ought to be operated based on visible-light-active semiconductors, which is very challenging. In this work, an F-expedited nitridation strategy is applied to modify the wide-bandgap semiconductor SrTiO for visible-light-driven photocatalytic overall water splitting.
View Article and Find Full Text PDFNat Commun
January 2025
State Key Laboratory of Photovoltaic Science and Technology, Department of Materials Science, Institute of Optoelectronics, Fudan University, Shanghai, 200433, China.
Ferroelectric semiconductors have the advantages of switchable polarization ferroelectric field regulation and semiconductor transport characteristics, which are highly promising in ferroelectric transistors and nonvolatile memory. However, it is difficult to prepare a Sn-based perovskite film with both robust ferroelectric and semiconductor properties. Here, by doping with 2-methylbenzimidazole, Sn-based perovskite [93.
View Article and Find Full Text PDFNat Commun
January 2025
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA.
Energy efficiency in computation is ultimately limited by noise, with quantum limits setting the fundamental noise floor. Analog physical neural networks hold promise for improved energy efficiency compared to digital electronic neural networks. However, they are typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR) is large (>10), and the noise can be treated as a perturbation.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Exscientia, Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
The development of machine-learning (ML) potentials offers significant accuracy improvements compared to molecular mechanics (MM) because of the inclusion of quantum-mechanical effects in molecular interactions. However, ML simulations are several times more computationally demanding than MM simulations, so there is a trade-off between speed and accuracy. One possible compromise are hybrid machine learning/molecular mechanics (ML/MM) approaches with mechanical embedding that treat the intramolecular interactions of the ligand at the ML level and the protein-ligand interactions at the MM level.
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